Understanding the COVID-19 Data Quality Problem with Sherri Rose - #374

Understanding the COVID-19 Data Quality Problem with Sherri Rose - #374

Today we’re joined by Sherri Rose, Associate Professor at Harvard Medical School. We cover a lot of ground in our conversation, including the intersection of her research with the current COVID-19 pandemic, the importance of quality in datasets and rigor when publishing papers, and the pitfalls of using causal inference. We also touch on Sherri’s work in algorithmic fairness, the shift she’s seen in fairness conferences covering these issues in relation to healthcare research, and a few recent pape

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Why Models Are AI’s Next Training Dataset with Damian Borth - #772

Why Models Are AI’s Next Training Dataset with Damian Borth - #772

For more than a decade, AI has advanced by training ever-larger models on ever-larger datasets. But as high-quality training data becomes harder to find and pretraining grows increasingly expensive, r...

27 Heinä 47min

How AI Learns to Smell with Alex Wiltschko - #771

How AI Learns to Smell with Alex Wiltschko - #771

In this episode, Alex Wiltschko, founder and CEO of Osmo, joins the show to discuss his goal of giving computers a sense of smell and what it takes to build olfactory intelligence. We explore the sci...

8 Heinä 59min

Why AI Agents Break the GenAI Security Model with Devvret Rishi - #770

Why AI Agents Break the GenAI Security Model with Devvret Rishi - #770

In this episode, Sam talks with Dev Rishi, GM of AI at Rubrik, about what happens when agents move beyond answering questions and start taking action across tools, systems, and business processes. We...

16 Kesä 56min

Is RAG Dead? Lessons from Building AI for Tax Law with Alex Bowcut - #769

Is RAG Dead? Lessons from Building AI for Tax Law with Alex Bowcut - #769

As context windows grow into the millions of tokens, many AI practitioners are questioning whether retrieval-augmented generation (RAG) is still necessary. If modern models can ingest entire libraries...

9 Kesä 51min

Relational Foundation Models for Enterprise Data with Jure Leskovec - #768

Relational Foundation Models for Enterprise Data with Jure Leskovec - #768

In this episode, Jure Leskovec, co-founder and chief scientist at Kumo and professor of computer science at Stanford, joins us to explore two fronts of his work: AI for science and relational deep lea...

21 Touko 1h 6min

How to Find the Agent Failures Your Evals Miss with Scott Clark - #767

How to Find the Agent Failures Your Evals Miss with Scott Clark - #767

In this episode, Scott Clark, co-founder and CEO of Distributional, joins us to explore how teams can reliably operate and improve complex LLM systems and agents in production. Scott introduces a Masl...

7 Touko 53min

How to Engineer AI Inference Systems with Philip Kiely - #766

How to Engineer AI Inference Systems with Philip Kiely - #766

In this episode, Philip Kiely, head of AI education at Baseten, joins us to unpack the fast-evolving discipline of inference engineering. We explore why inference has become the stickiest and most cri...

30 Huhti 54min

How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765

How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765

In this episode, Rashmi Shetty, senior director of enterprise generative AI platform at Capital One, joins us to explore how the company is designing, deploying, and scaling multi-agent systems in a h...

16 Huhti 54min

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